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    <title>topic Regression Technique in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339441#M17875</link>
    <description>&lt;P&gt;If your dependent variable is a&amp;nbsp;&lt;EM&gt;continuous&amp;nbsp;&lt;/EM&gt;variable but is bounded between 0 and 100, what type of regression analysis would work best?&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 08 Mar 2017 21:06:21 GMT</pubDate>
    <dc:creator>buder</dc:creator>
    <dc:date>2017-03-08T21:06:21Z</dc:date>
    <item>
      <title>Regression Technique</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339441#M17875</link>
      <description>&lt;P&gt;If your dependent variable is a&amp;nbsp;&lt;EM&gt;continuous&amp;nbsp;&lt;/EM&gt;variable but is bounded between 0 and 100, what type of regression analysis would work best?&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 08 Mar 2017 21:06:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339441#M17875</guid>
      <dc:creator>buder</dc:creator>
      <dc:date>2017-03-08T21:06:21Z</dc:date>
    </item>
    <item>
      <title>Re: Regression Technique</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339449#M17876</link>
      <description>&lt;P&gt;Assuming that your dependent variable is a percentage, you should consider transforming it for doing regression. Good documentation on this topic is given in SAS/IML doc &amp;nbsp;:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/documentation/cdl/en/imlsug/66113/HTML/default/viewer.htm#imlsug_ugvartransform_sect007.htm" target="_self"&gt;http://support.sas.com/documentation/cdl/en/imlsug/66113/HTML/default/viewer.htm#imlsug_ugvartransform_sect007.htm&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;EM&gt;arcsin(sqrt(y))&lt;/EM&gt; (where &lt;EM&gt;y&lt;/EM&gt; is between 0 and 1) is the preferred transformation when the denominators of the proportions are within the same order of magnitude.&lt;/P&gt;</description>
      <pubDate>Wed, 08 Mar 2017 21:45:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339449#M17876</guid>
      <dc:creator>PGStats</dc:creator>
      <dc:date>2017-03-08T21:45:02Z</dc:date>
    </item>
    <item>
      <title>Re: Regression Technique</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339450#M17877</link>
      <description>&lt;P&gt;Thanks! The depdenent variable is not a percentage, it's a ranking (0 is lowest, 100 is highest and have values all throughout).&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;But I assume I could divide all variable by 100 and use that technique?&lt;/P&gt;</description>
      <pubDate>Wed, 08 Mar 2017 21:47:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339450#M17877</guid>
      <dc:creator>buder</dc:creator>
      <dc:date>2017-03-08T21:47:21Z</dc:date>
    </item>
    <item>
      <title>Re: Regression Technique</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339536#M17884</link>
      <description>&lt;PRE&gt;
I could try GAMMA distribution.
Check the example of GENMOD.

Example 44.3: Gamma Distribution Applied to Life Data



&lt;/PRE&gt;</description>
      <pubDate>Thu, 09 Mar 2017 04:23:15 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Technique/m-p/339536#M17884</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2017-03-09T04:23:15Z</dc:date>
    </item>
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